Original summary:
The MERGE project will perform a throughout assessment of the behaviour of electric power systems with a large penetration of electric vehicles (Evs). Management and control strategies as well as regulatory frameworks for the appropriate integration of Evs will be developed. Several software tools will be used for these purposes.
WP2 of the MERGE project deals with the adaptation and enhancement of the existing tools that are required to address the integration of Evs into electric power systems. These tools all together will form an evaluation suite needed to achieve the objective of the project.
Deliverable 2.4 presents the work done within Task 2.6 “Estimation of additional investment cost in the distribution networks with high penetration of electric plug-in vehicles”. In this task, two distribution planning models developed by the (Institute for Research in Technology) IIT of Comillas University have been updated so as to allow for the evaluation the need for investments and grid reinforcements due to the introduction of Evs. These models are
generically referred to as reference network models (RNMs), being one of them a greenfield RNM and the other a expansion-planning RNM. RNMs must be able to measure the impact of the introduction of EV on system losses and quality of service.
This document describes the functionalities of RNMs as well as their inputs, outputs and internal algorithms. It is shown that a greenfield RNM can design a quasi optimal distribution network from scratch for very large distribution areas given the transmission substations and the end-consumers and other network users such as distributed generators (DG) or Evs.
Similarly, the expansion-planning RNM can design a reference network but starting from a given initial grid which can either correspond to the actual network or a reference network obtained with the greenfield RNM. RNMs consider both technical constraints (voltage limits, thermal capacity, etc.) and geographical constraints (forbidden regions, street maps and orography). As a result, the RNMs provide all the technical and economic information of the
network obtained as well as the energy losses incurred broken down per voltage levels.
Finally, the modifications performed in order to measure the impact of Evs on distribution investments and operational issues have been detailed. Traditionally, distribution networks were designed according to the peak demand. However, the future large penetration of Evs and DG will require grid planners to consider a wider range of possible situations, such as peak local generation. Similarly, distribution planning models ought to be adapted. Following this line, the RNMs have been upgraded so as to allow them to design reference networks for very large areas considering several scenarios. Thanks to this modification, the impact of different battery charging strategies throughout the day on distribution networks can now be assessed more precisely.
English summary:
The MERGE project will perform a throughout assessment of the behaviour of electric power systems with a large penetration of electric vehicles (EVs). Management and control strategies as well as regulatory frameworks for the appropriate integration of EVs will be developed. Several software tools will be used for these purposes.
WP2 of the MERGE project deals with the adaptation and enhancement of the existing tools that are required to address the integration of EVs into electric power systems. These tools all together will form an evaluation suite needed to achieve the objective of the project.
Deliverable 2.4 presents the work done within Task 2.6 “Estimation of additional investment cost in the distribution networks with high penetration of electric plug-in vehicles”. In this task, two distribution planning models developed by the (Institute for Research in Technology) IIT of Comillas University have been updated so as to allow for the evaluation the need for investments and grid reinforcements due to the introduction of EVs. These models are
generically referred to as reference network models (RNMs), being one of them a greenfield RNM and the other a expansion-planning RNM. RNMs must be able to measure the impact of the introduction of EV on system losses and quality of service.
This document describes the functionalities of RNMs as well as their inputs, outputs and internal algorithms. It is shown that a greenfield RNM can design a quasi optimal distribution network from scratch for very large distribution areas given the transmission substations and the end-consumers and other network users such as distributed generators (DG) or EVs.
Similarly, the expansion-planning RNM can design a reference network but starting from a given initial grid which can either correspond to the actual network or a reference network obtained with the greenfield RNM. RNMs consider both technical constraints (voltage limits, thermal capacity, etc.) and geographical constraints (forbidden regions, street maps and orography). As a result, the RNMs provide all the technical and economic information of the
network obtained as well as the energy losses incurred broken down per voltage levels.
Finally, the modifications performed in order to measure the impact of EVs on distribution investments and operational issues have been detailed. Traditionally, distribution networks were designed according to the peak demand. However, the future large penetration of EVs and DG will require grid planners to consider a wider range of possible situations, such as peak local generation. Similarly, distribution planning models ought to be adapted. Following this line, the RNMs have been upgraded so as to allow them to design reference networks for very large areas considering several scenarios. Thanks to this modification, the impact of different battery charging strategies throughout the day on distribution networks can now be assessed more precisely.
IIT Project: MERGE_EU_FP7 (MERGE)
Funding entity: Comisión Europea. FP7 - Cooperation / Energy
Publication date: 10-01-2011
IIT-11-219I
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